Title :
Crime Incident Association with Consideration of Narrative Information
Author :
Wang, Xiaofeng ; Brown, Donald E. ; Conklin, James H.
Author_Institution :
Univ. of Virginia, Charlottesville
Abstract :
Law enforcement agencies need to discover underlying patterns of crimes in a short time. One of the key steps is associating related criminal incidents with each other. This paper describes a new methodology to associate crime incidents automatically, as well as, accurately by using narrative information. Specifically this paper shows a new method for measuring the similarity between crime incident narratives. Evaluations show that our method could measure similarity between narrative information quickly and accurately. In addition, a toolkit based on this methodology was developed to perform crime incident association.
Keywords :
data mining; law administration; police data processing; crime incident association; law enforcement agency; narrative information; pattern discovery; Biomedical measurements; Data engineering; Data mining; Electronic mail; Frequency; Information analysis; Information retrieval; Systems engineering and theory; Text categorization; Text mining;
Conference_Titel :
Systems and Information Engineering Design Symposium, 2007. SIEDS 2007. IEEE
Conference_Location :
Charlottesville, VA
Print_ISBN :
978-1-4244-1286-0
Electronic_ISBN :
978-1-4244-1286-0
DOI :
10.1109/SIEDS.2007.4373987
